François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ? How do we govern all these data products and domains ? In this stage, you will never think about the configuration.

Architecture 130

Architecture Technology Google Cloud Metadata 130

Knowledge Hut

MARCH 28, 2024

Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance. Develop data models, data governance policies, and data integration strategies. Familiarity with ETL tools and techniques for data integration.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

SEPTEMBER 20, 2022

Here’s how Prefect , Series B startup and creator of the popular data orchestration tool, harnessed the power of data observability to preserve headcount, improve data quality and reduce time to detection and resolution for data incidents. But a growing company means growing data needs. Scaling data governance.

Big Data 52

Big Data Data Warehouse Data Data Governance 52

Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Data lakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs.

Consulting 123

Consulting Machine Learning Data Science Data Pipeline 123

phData: Data Engineering

JANUARY 3, 2022

This commonly introduces: Database or Data Warehouse API/EDI Integrations ETL software Business intelligence tooling By leveraging off-the-shelf tooling, your company separates disciplines by technology. Instead of manually working with the data, software, and data products, extract the data to unlock the ability to generate insights.

IT 52

IT AWS Software Engineer Software Engineering 52